Tumor Nonimmune-Microenvironment-Related Gene Expression Signature Predicts Brain Metastasis in Lung Adenocarcinoma Patients after Surgery: A Machine Learning Approach Using Gene Expression Profiling.
Seokjin HaamJae-Ho HanHyun Woo LeeYoung Wha KohPublished in: Cancers (2021)
Using a machine learning approach with a gene expression profile, we discovered a tumor nonimmune-microenvironment-related gene expression signature, including extracellular matrix (ECM) remodeling, epithelial-mesenchymal transition (EMT), and angiogenesis, that could predict brain metastasis (BM) after the surgical resection of 64 lung adenocarcinomas (LUAD). Gene expression profiling identified a tumor nonimmune-microenvironment-related 17-gene expression signature that significantly correlated with BM. Of the 17 genes, 11 were ECM-remodeling-related genes. The 17-gene expression signature showed high BM predictive power in four machine learning classifiers (areas under the receiver operating characteristic curve = 0.845 for naïve Bayes, 0.849 for support vector machine, 0.858 for random forest, and 0.839 for neural network). Subgroup analysis revealed that the BM predictive power of the 17-gene signature was higher in the early-stage LUAD than in the late-stage LUAD. Pathway enrichment analysis showed that the upregulated differentially expressed genes were mainly enriched in the ECM-receptor interaction pathway. The immunohistochemical expression of the top three genes of the 17-gene expression signature yielded similar results to NanoString tests. The tumor nonimmune-microenvironment-related gene expression signatures found in this study are important biological markers that can predict BM and provide patient-specific treatment options.
Keyphrases
- gene expression
- genome wide
- dna methylation
- genome wide identification
- machine learning
- extracellular matrix
- epithelial mesenchymal transition
- copy number
- early stage
- stem cells
- transcription factor
- neural network
- end stage renal disease
- genome wide analysis
- chronic kidney disease
- endothelial cells
- deep learning
- clinical trial
- radiation therapy
- peritoneal dialysis
- long non coding rna
- randomized controlled trial
- newly diagnosed
- brain injury
- squamous cell carcinoma
- rectal cancer
- patient reported outcomes